Senior Cloud Architect, ML/AI
Location Our Senior Cloud Architect will be an integral part of our Cloud Reliability Engineering team in the UK, Ireland, Estonia, Netherlands, Sweden and Spain. The role is also available to contractors in other Eastern European locations / Portugal.
Who We Are DoiT is a global technology company that works with cloud-driven organizations to leverage the cloud to drive business growth and innovation. We combine data, technology, and human expertise to ensure our customers operate in a well-architected and scalable state - from planning to production.
Delivering DoiT Cloud Intelligence, the only solution that integrates advanced technology with human intelligence, we help our customers solve complex multicloud problems and drive efficiency.
With decades of multicloud experience, we have specializations in Kubernetes, GenAI, CloudOps, and more. An award-winning strategic partner of AWS, Google Cloud, and Microsoft Azure, we work alongside more than 4,000 customers worldwide.
The Opportunity As a Senior Cloud Architect, you will be part of our global CRE team, working with rapidly growing companies in EMEA and around the world. This role offers you the chance to:
- Apply your hands-on experience & skills in a consultative manner to address our customers’ strategic and tactical needs around cloud technologies
- Grow your technical and interpersonal skills by addressing customer challenges in your daily work and leveraging dedicated time allocated by the company for learning new technologies and engaging in internal initiatives
- Strengthen your personal brand through thought leadership activities such as blogging, public speaking, and participation in technology events
What we offer
- Unlimited Vacation
- Flexible Working Options
- Health Insurance
- Parental Leave
- Employee Stock Option Plan
- Home Office Allowance
- Professional Development Stipend
- Peer Recognition Program
Many Do’ers, One Team DoiT unites as Many Do’ers, One Team, where diversity is more than a goal—it's our strength. We actively cultivate an inclusive, equitable workplace, recognizing that each unique perspective enhances our innovation. By celebrating differences, we create an environment where every individual feels valued, contributing to our collective success.
Qualifications
Experience Requirement:
- Minimum of 4+ years of experience in architecting, deploying, and managing cloud-based AI/ML solutions.
Core AWS Expertise:
- Expertise in architecting, developing, and troubleshooting large production-grade distributed systems on AWS, and selecting the appropriate tools to address business problems at the correct scale.
- Advanced proficiency in AWS, with a focus on Generative AI and machine learning services. Certified AWS Solutions Architect Professional and/or AWS Machine Learning Specialty
- Proven track record of architecting, deploying, and optimizing complex cloud solutions for AI-driven workloads.
Generative AI and Cutting-Edge Technologies:
- Expertise in Amazon Bedrock for deploying foundation models and managing scalable GenAI workloads.
- Proficiency in fine-tuning and deploying Large Language Models (LLMs) and multimodal AI using Amazon SageMaker JumpStart and Hugging Face on AWS.
- Experience leveraging Amazon Q (formerly AWS CodeWhisperer) Business and Developer for AI-powered coding productivity and automation.
Machine Learning Frameworks and Pipelines:
- In-depth knowledge of Amazon SageMaker, including Pipelines, Model Monitor, Data Wrangler, and SageMaker Clarify for bias detection and interpretability.
- Skilled in distributed model training with multi-GPU clusters and optimization for high-performance inference.
Data Engineering and AI Workflow Optimization:
- Proficient in building data pipelines with Amazon S3, AWS Glue, Lake Formation, and Redshift for AI and ML workloads.
- Experienced in optimizing data preparation for large-scale AI model training and inference workflows.
AI Integration and Deployment:
- Expertise in building end-to-end AI pipelines using AWS Lambda, Step Functions, and API Gateway for real-time AI inference and automation.
- Familiarity with containerized AI deployments using Amazon EKS and AWS Fargate.
DevOps and MLOps Expertise:
- Hands-on experience with CI/CD pipelines for AI/ML workflows using AWS CodePipeline, CodeBuild, and SageMaker Pipelines.
- Proficiency in monitoring and maintaining AI systems with Amazon CloudWatch and SageMaker Model Monitor.
AI Governance and Security:
- Strong understanding of AI governance, incorporating IAM, AWS Key Management Service (KMS), and compliance frameworks.
- Knowledgeable in AI ethics, bias detection, and accountability using tools like SageMaker Clarify.
Emerging AI Trends:
- Up-to-date on Generative AI advancements such as RLHF (Reinforcement Learning with Human Feedback), foundation model fine-tuning, and hybrid AI architectures.
- Familiarity with integrating open-source tools like Hugging Face Transformers and AWS-native solutions.
Knowledge of Multi-Cloud AI Tools:
- Good knowledge and understanding of Google Cloud AI tools such as Vertex AI, Cloud AutoML, and BigQuery ML, enabling effective integration in multi-cloud environments.
Mentoring and Enablement Skills:
- Proven ability to mentor team members and enable cross-functional collaboration to foster technical growth and innovation.
- Skilled in creating knowledge-sharing platforms and hands-on workshops to enhance team capabilities.
Bonus Points
- Passion for technology, with a demonstrated ability to quickly learn and stay up to date with industry trends.
- Data certification is a major advantage (e.g., Stanford, Coursera, Udacity, MIT, eCornell, or any Data certification with AWS/GCP).
- BA/BS degree in Computer Science, Mathematics, Economics, or a related technical field, or equivalent practical experience.
